Degree:
MSc if Mathematics from the University of Stockholm
Short Bio:
After finishing his MSc at Stockholm University Daniel Witschard worked several years in software development with focus on applications for Visual Analytics on Big Data. The hands-on proficiency from the starting years as a C++ programmer, combined with the management experience from later years project leader and management positions, has given a profound understanding of the many challenges of the field. Given the opportunity to tackle the research frontier of Data Visualization and Visual Analytics Daniel gladly joined the LNU/ISOVIS research group as a PhD student.
Research
Daniel focuses on Visual Analytics on Multivariate Networks (MVNs, i.e., large networks with considerable amounts of associated data). By exploring ways to combine several different embedding technologies the main goal is to find new, and better, ways to perform similarity calculations on large and complex entities. If successful, the results may also be possible to generalize beyond the scope of MVNs.
My ongoing research projects
Publications
Article in journal (Refereed)
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Witschard, D., Jusufi, I., Kucher, K., Kerren, A. (2025). Visually Guided Extraction of Prevalent Topics. Information Visualization.
Status: Epub ahead of print -
Huang, Z., Witschard, D., Kucher, K., Kerren, A. (2023). VA + Embeddings STAR : A State-of-the-Art Report on the Use of Embeddings in Visual Analytics. Computer graphics forum (Print). 42 (3). 539-571.
Status: Published -
Witschard, D., Jusufi, I., Martins, R.M., Kucher, K., Kerren, A. (2022). Interactive Optimization of Embedding-based Text Similarity Calculations. Information Visualization. 21 (4). 335-353.
Status: Published
Conference paper (Refereed)
- Witschard, D., Jusufi, I., Kucher, K., Kerren, A. (2023). Visually Guided Network Reconstruction Using Multiple Embeddings. Proceedings of the 16th IEEE Pacific Visualization Symposium (PacificVis '23), visualization notes track, IEEE, 2023. 212-216.
- Witschard, D., Jusufi, I., Martins, R.M., Kerren, A. (2021). A Statement Report on the Use of Multiple Embeddings for Visual Analytics of Multivariate Networks. Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP. 219-223.
- Witschard, D., Jusufi, I., Kerren, A. (2021). Dynamic Ranking of IEEE VIS Author Importance. Poster Abstract, IEEE Visualization and Visual Analytics (VIS '21).
- Witschard, D., Jusufi, I., Kerren, A. (2021). SimBaTex : Similarity-based Text Exploration. Posters of the 23rd EG/VGTC Conference on Visualization (EuroVis '21). 5-7.
Conference paper (Other academic)
- Witschard, D., Jusufi, I., Martins, R.M., Kerren, A. (2020). Multiple Embeddings for Multivariate Network Analysis. 6th annual Big Data Conference at Linnaeus University, in Växjö, Sweden.
Licentiate thesis, monograph (Other academic) (Other academic)
- Witschard, D. (2022). Towards Multiple Embeddings for Multivariate Network Analysis. Licentiate Thesis. Linnaeus University Press. 72.